Watch Python Data Visualization | Matplotlib | Seaborn | Plotly : Create Column and Bar Chart. Video Tutorial

In this session, we are going to discuss about Column chart and Bar using Python Matplotlib with numerous examples in greater details. Column and Bar chart are easy to use for showing data changes over a period of time and draw the comparisons for amount, categories, items etc. A column chart is distinct from a bar chart. While a bar chart plots the variable horizontally and the fixed dimension vertically, the column chart does the opposite. What you will learn: 1.) How to create a bar chart with x-label, y-label, and title? 2.) Matplotlib's styles offer features such as colors, width, border style, transparency (alpha), labels and annotations, legends, and gridlines. 3.) How to change the figure size using plt.subplots? 4.) How to add data labels to a column and bar chart? 5.) What is the meaning of vertical alignment (va) and horizontal alignment (ha)? 6.) How to add a legend to a chart with a customized location such as best, upper right, upper left, lower left, lower right, right, center left, center right, lower center, upper center, and center? 7.) How to add millions of colors to a chart using hexadecimal codes? 8.) How to make hexadecimal colors using MS-Excel? 9.) How many styles are available in Matplotlib, and can you print all the styles? 10.) How to create a column chart and bar chart together in a single plot using nrows and ncols? 11.) How to add error bars to a bar chart? 12.) What is the difference between a bar chart and a column chart? 13.) What are the best practices for using these charts, and when should you use them? 14.) Examples... Github link for Jupyter Notebook: https://tinyurl.com/2gjdzo26 Telegram Link: https://t.me/+32-TodtiOvo2Njk9